The present invention relates to a pattern inspecting apparatus for inspecting a defect of an electronic circuit pattern formed on a semiconductor wafer, and in particular, to a defect-inspection control system of an electronic circuit pattern, a defect inspecting system and an defect inspecting apparatus of an electronic circuit pattern, by which man-hours set by inspection parameters (inspection conditions) in a pattern inspecting apparatus are reduced according to design information including layout data, and by which defect information detected by the pattern inspecting apparatus is managed.
While a lifetime of a semiconductor product is being shortened, and while a shift toward a multi-product production system is being performed mainly in a field of system LSI, a demand for early establishment of mass-production process conditions are more and more being increased. A defect inspecting apparatus is extremely important as a tool that inspects appearance in each process of semiconductor production, and that acquires information about a state, in which a defect occurs, to get an instruction to adjust process conditions, or to detect malfunction of a process state. As semiconductor appearance inspecting apparatuses that have already been put into practice, there are an optical foreign-material inspecting apparatus, and an optical or an electron-beam pattern inspecting apparatus, and an optical or an electron-beam defect reviewing apparatus.
As a conventional example in which a defect of an electronic circuit pattern formed on a semiconductor wafer is inspected, for example, an optical wafer defect inspecting apparatus that is described in Japanese Patent Application Laid-Open No. Sho 62-43505, and an electron beam defect reviewing apparatus that was described in Japanese Patent Application Laid-Open No. Hei 10-135288, are known. When inspecting a defect of an electronic circuit pattern using these defect inspecting apparatuses, a user is required to set and adjust various inspection parameters including set conditions of an optical system. After describing an outline of inspection for these inspecting apparatuses, setting of the inspection parameters will be described below.
In the first place, as a first example of the prior art, optical defect-inspecting technology will be described with reference to FIG. 27.
In the figure, to begin with, a semiconductor wafer 121 as an object to be inspected is secured on a stage 120. Then, while moving the stage 120, a surface of the semiconductor wafer 121 is light-scanned. Reflected light from the surface of this semiconductor wafer 121 is detected by a detector 123 through a detection optical system 122. The detected output is then stored in a memory 124 as digital data.
On the semiconductor wafer 121, a chip pattern is repeatedly copied at fixed intervals. After an image of an object point 127 to be inspected on the semiconductor wafer 121 (hereinafter the image is referred to as defect image because it is an image as an object for which a defect is inspected) is detected, and stored in the memory 124 as digital data, an image of a point 128 having the same pattern in an adjacent chip is detected as a reference image, and is stored in a memory 25. A comparator 126 compares the defect image 127 and the reference image 128, which have been stored in the memories 124 and 125, respectively, and then extracts and outputs a defect.
The example described above relates to a case where an image of the same point in an adjacent chip is detected for use as a reference image. However, in a case where a repeated pattern portion such as a memory (hereinafter referred to as cell portion) is inspected, an image, which is shifted by a repeated period, may be used. Usually, in a cell portion, as compared with comparison at the same point on a physically apart adjacent chip, comparison with an area, of which a repeated unit is shifted by one period, enables an inspection with high sensitivity. This is because as regards a difference image between the reference image and the defect image, brightness distribution of a normal portion tends to decrease, as they get nearer physically, which results in a large difference in signal intensity between the defect portion and the normal portion in an image. This can be explained by the fact that a shape gap of a pattern becomes smaller as they get nearer physically, or that a difference in coherent light intensity caused by a surface film becomes smaller as they get nearer physically, or the like.
Usually, a method, in which an image shifted by one repeated period in a repeated pattern portion is used as a reference image, is called a cell comparison method; and a method, in which an image detected at the same point in an adjacent chip is used as a reference image, is called a die comparison method.
FIG. 28 is an explanatory diagram illustrating comparison operation in the comparator 126 shown in FIG. 27. Reference numeral 130 denotes a defect image, and 131 denotes a reference image.
To be more specific, comparison logical operation is performed for binarized images 132 and 133, which have been obtained by classification into black and white according to whether or not a brightness value of an image is higher than a fixed value (=binarization threshold value), to get a comparison result 134. In this comparison result 134, not only a defect but also a component 134a caused by dispersion in pattern shape between the defect image 130 and the reference image 131, and a component 134b caused by noise are produced. Usually, detection of a component except such a defect area causes a false report. Therefore, noise removal processing is performed. Noise removal can be achieved by the following: for example, if a diameter is smaller than or equal to a fixed value (hereinafter referred to as a noise removal threshold value) in binarization images, considering it to be noise, and removing the noise. As a result of noise removal processing, as is the case with the processing result 135, only the defect is extracted.
As described above, as regards the die comparison method, noise is produced more easily than the cell comparison method. Therefore, the noise removal threshold value is required to be larger than that of the cell comparison method. This means that the defect that is smaller than a noise removal threshold value cannot be detected.
In the above description, the binarization threshold value and the noise removal threshold value, which have been described above, are called inspection parameters (inspection conditions). Setting of the inspection parameters will be described below.
FIG. 29 is a diagram illustrating an example of a screen for setting typical inspection parameters.
In the same figure, an inspection-parameter setting screen displays a wafer map 140, which explicitly shows a chip as an object to be inspected, and a cell-area setting screen 141, which magnifies the chip as the object to be inspected for displaying the chip. A user can inspect a cell area in the chip by using an inspection parameter which is different from a non-cell area, by surrounding the cell area (cell portion) 142 with a broken line in the cell-area setting screen 141 to select the cell area. To be more specific, after the cell area 142 is selected, various inspection parameters such as a detection optical system parameter or an image processing parameter in the cell area 142 are directly inputted by the manual operation on GUI, and in succession, inspection parameters of a non-cell area except the cell area is directly inputted by the manual operation on GUI in a similar manner. In the cell area 142, setting a noise removal threshold value to be smaller than the non-cell portion enables an inspection with sensitivity higher than that of the non-cell portion.
Next, procedures for setting a cell area by the manual operation will be described.
The cell area 142 is set by the following operation: placing a cursor at a desired position in a circumferential portion of an area, which is intended for the cell area 142, on the cell-area setting screen 141; clicking a mouse to define the position as a vertex of the cell area 142; and repeating the defining operation for each vertex to define a vertex group of the cell area 142. In this method, there is also a case where cell areas are dispersively located at ten positions or more in a chip area. Therefore, the manual setting is required for each cell area one by one.
Next, an electron beam type defect reviewing apparatus will be described as a second example of the prior art.
In contrast to the pattern inspecting apparatus described as the first example of the technology, which is intended for a wafer where a state in which a defect occurs is unknown, a defect reviewing apparatus detects an image of a defect position again for a wafer, of which a defect position has already been identified by a pattern inspecting apparatus, for the purpose of observing the defect in more detail.
That is to say, in the first place, the wafer is inspected by the pattern inspecting apparatus as described above, and thereby the defect position is detected. Output information of the pattern inspecting apparatus includes simple information about a defect such as a defect position on a wafer and an outline of a size.
Usually, as regards defect detection by the pattern inspecting apparatus, for the purpose of shortening inspection time, an image is not detected with magnification high enough to observe its detail as compared with a size of a defect.
The defect reviewing apparatus picks up an image of a defect position on a wafer, and a reference image corresponding to this image, with magnification high enough to observe a defect in detail using output information of a pattern inspecting apparatus as an input. Image-pickup magnification is one of the inspection parameters, which are predetermined by a user. An image is picked up with specific magnification, which has been predetermined for all defects.
Next, manual parameter-setting procedures in the defect inspecting apparatus will be described.
Such parameters are roughly classified into a parameter (hereinafter referred to as image detection parameter) which sets image pickup conditions, and a parameter (hereinafter referred to as image processing parameter) which sets image processing conditions.
A typical flowchart illustrating manual inspection-parameter setting procedures on the defect reviewing apparatus will be described. To begin with, an area to be inspected is set. The area to be inspected is defined by inputting data such as a chip layout and a chip size on a semiconductor wafer surface. Moreover, as regards some defect inspecting apparatuses, a chip is divided into a plurality of partial inspection areas (such as a cell area, and a non-cell area) for setting.
An area to be inspected is manually set using the following procedures. The above-mentioned partial inspection area, which is divided, is considered to be a rectangular for example. While displaying an image, which has been picked up on a sample surface, on an operation screen, an operator moves a stage, on which a semiconductor wafer is mounted, so that a vertex of a rectangle enters a visual field, in order to specify a rectangular partial inspection area by the manual operation. Then, the user manually specifies a vertex position of the rectangle by using a cursor, or the like on GUI as shown in FIG. 29. Performing similar manual operation for each vertex of the rectangle enables setting of the partial inspection area on the rectangle. If there are a plurality of partial inspection areas, it is necessary to perform the manual setting operation of a rectangular area repeatedly.
Next, the operator manually sets image detection parameters temporarily, detects an image at a position appropriately selected from the area to be inspected, and then judges whether or not image quality is good by a visual inspection on GUI. In this case, if the image quality is not good, the image detection parameters are manually set again.
Next, as regards the image detection parameter, which has been set, the operator manually sets image processing parameters temporarily on GUI, and executes a temporary inspection. After executing the inspection, the operator checks a position of a detected defect, and inspects a state in which the image processing parameters are set. If there are more false reports than expected, this means that sensitivity is too high. Therefore, the sensitivity is reduced. On the other hand, if the number of detected defects is too few, or if a standard defect could not be detected, the sensitivity is increased.
Each manual operation of resetting of the image processing parameters, re-execution of a temporary inspection, and a recheck of an inspection result is executed repeatedly until the parameter adjustment is completed, and until desired conditions for judgment are satisfied as follows: the number of false reports becomes a fixed number or less; or the number of false reports becomes a fixed number or less within a range that a standard defect is found; or the like.
As described as the prior art, including selection which method should be executed (the cell comparison method or the die comparison method), concerning general inspection parameters, even if the operator tries to divide an area to be inspected into many partial inspection areas, and tries to set a different inspection parameter for each partial inspection area, setting of each partial inspection area is forced to depend on manpower, which hinders efficient setting. Division by manual operation into many partial inspection areas of which an inspection parameter is different substantially, and an inspection by manual setting the inspection parameter which is different for each partial inspection area, become impossible substantially. This is disadvantageous in the following points.
Firstly, explosive increase in the number of detected defects cannot be avoided. Depending on pattern density, a size of a fatal defect is different. To be more specific, if pattern density is high, it is important that even a defect having a smaller size can be detected reliably. Nevertheless, if defect detection sensitivity is manually set high enough to be appropriate to an area where a pattern is dense, and if this is applied to an entire surface of an area to be inspected, the number of detected defects will become 1000 or more, resulting in difficult control.
Secondly, inspection parameters cannot be optimized for each position. As an example of inspection parameters, critical parameters as described above are mentioned.
Other than the example, as regards parameters related to image detection conditions, if a defect reviewing apparatus, which has been introduced as the second example of the prior art, is described as an example, a defect size, which is the most important for control, is determined depending on roughness and fineness of a pattern as described above. Image-pickup magnification, which is used when detecting an image, should be set so that a defect having this image size is suited for a pickup image size. However, under present circumstances, because an image is detected at fixed image-pickup magnification, a case where magnification becomes too low or too high as compared with a defect size often arises.
In addition, as regards the conventional procedures, there is a problem that manual setting of an area to be inspected requires great efforts. Conventionally, when a chip area is divided by manual operation into a plurality of partial areas, such as a cell area and a non-cell area, if a number of divisions is large, manual setting of an area to be inspected becomes difficult substantially. Moreover, there is also a problem that manual setting and manual adjustment of parameters for each divided partial inspection area require great efforts.
As described above, it is important to divide an area to be inspected into a plurality of partial inspection areas so that an inspection parameter, which is different for each partial inspection area, is set for an inspection. Or, it is important to set an inspection parameter for a specific pattern in an area to be inspected to inspect the specific pattern. However, conventionally, there was the problem that great efforts are required for realizing it, or that it cannot be realized practically.